📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI for Air Quality Monitoring: Predictive Models for Urban Health, from foundations to a certified capstone project.
Outline
Explore health impacts of PM2.5, NOx, SO₂, CO • Gather data from IoT sensors, stations, satellites • Preprocess time‑series data using Python (Pandas, NumPy)
Outline
Engineer features from weather, traffic, and historical pollution • Train regression & time‑series models (ARIMA, LSTM, Random Forest) • Evaluate models with RMSE, MAE and tune performance
Outline
Design AI‑based pollution mitigation strategies • Create interactive visual dashboards for real‑time alerts • Generate geographic risk maps pinpointing hotspots
Earn government-registered certification in AI for Air Quality Monitoring: Predictive Models for Urban Health
e-Certificate and e-Marksheet issued on successful completion.
